MétaCan
Menu
Back to cohort
Record W2125853789 · doi:10.2514/6.2012-4790

Two-dimensional airfoil shape optimization for airfoils at low speeds

2012· article· en· W2125853789 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA Modeling and Simulation Technologies Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAirfoilComputer scienceAerospace engineeringMaterials sciencePhysicsMechanicsEngineering

Abstract

fetched live from OpenAlex

This paper presents a fast methodology for the design of two-dimensional low-speed airfoils. We propose a methodology in which the design process starts from an already known airfoil or from a new defined airfoil by imposing some basic geometrical characteristics, such as: the airfoil’s radius at the leading edge, the maximum height of the airfoil’s lower and upper sides, the slopes of the airfoil’s defining curves at the trailing edge and the trailing edge gaps. Based on the above initial geometry the airfoil shape is further parameterized by use of Bezier or Bspline curves, the relative merit of the two types of parameterization is carefully analyzed and exemplified in the results section. The control points of the defining curves can be used to optimize the shape of the airfoil. The Xfoil flow solver was used for the aerodynamical calculations, and Matlab’s fmincon was used as the optimizer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.249
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it